computer tech security and public policy

Digital computer security and connected IoT smart  everything have become public policy priorities in an increasingly digital and data-dependent always on and connected economy and society.

edge or fog computing coming on strong in 2020

What is this edge or fog computing trend ? 

Both edge and fog computing provide similar functionalities where smart devices or items or sensors push data and analytics to cloud platforms.

“Fog computing and edge computing are effectively the same thing." 

 Both are concerned with leveraging the computing capabilities within a smaller simpler server / gateway or sensor hardware device and process and share data via a localized network to carry out computation tasks that would ordinarily have been carried out in the cloud. More advanced AI and data processing still are done on the cloud.   

Both technologies can help organizations reduce their reliance on cloud-based platforms to analyze data, provide intelligent automation and analysis.

The main difference between edge computing and fog computing comes down to where the processing of that data takes place.

Edge computing usually occurs directly on the devices to which the sensors are attached or a gateway device that is physically “close” to the sensors. 

Fog computing moves the edge computing activities to processors that are connected to the LAN or into the LAN hardware itself so they may be physically more distant from the sensors and actuators. Think NB-IoT or LoRa or mesh networks and those types of IoT technologies.   

Smart city IoT is here ...

Pagarba (pagarba.io) worked on some real time location tracking sensors and data collection projects.   We've been diving into radio frequencies, Lora , lorawan and private decentralized mesh networks lately to build better smarter Internet of things systems.  Good stuff. Interesting city.

" Wireless sensors can be used to monitor traffic data and analytics.  An ongoing pilot program on lower Union Street aims to count vehicles with the goal of reducing flow and idling. Traffic patterns differ between sport utility vehicles and compact cars. With a better understanding of the types of vehicles on city streets, the city can schedule traffic lights more efficiently. Data will also allow vehicles can be re-routed in the event of a crash or some other kind of large-scale event. "

https://dailygazette.com/article/2019/07/27/what-do-we-know-about-smart-cities

GraphQL and graph databases.

Four basics behind a graph database are

Nodes: The primary data elements

Relationships: How two nodes are connected

Nodes may have multiple relationships

Properties: Attributes of a node or of a relationship

Labels: How nodes are described and grouped together as sets

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Nodes may have multiple labels

Labels get indexed and optimized, making it easier for them to be quickly located

Graph databases shift the focus of their data models to the relationships, which makes retrieving complex data structures much easier.

They abstract nodes and relationships into one structure.

But what is GraphQL ?

https://www.upwork.com/hiring/development/why-facebooks-graphql-language-should-be-on-your-radar/

Graph databases

RDBMS, also known as Relational databases, are  structured and easy to query with a language like SQL, but they have limitations when it comes to unstructured data. And scaling usually means buying far more servers and even then , that has limitations.

Not all data, however, is that easily organized. Semi and Unstructured data like IoT sensor data, social media,.  photos, videos, location-based GIS information, web or mobile activity, and usage metrics can’t be neatly broken down nor should be, but nobody wants a data swamp. 

Things like Hadoop, HBase, Cassandra, MongoDB and other NoSQL or NewSQL like databases trade tables for documents or json or blocks or columnar like schemas and more.  

https://www.business2community.com/brandviews/upwork/the-importance-of-graph-databases-in-an-increasingly-connected-world-02094654

How will Blockchain Change the World ?

How will Blockchain Change the World ? 

     Blockchain, bitcoin, Ethereum, Litecoin, Ripple, Monero and the like are changing the world as we speak...

    However they also aren't exactly being used for much more than speculative investments. Or silk road like transactions. Or Ponzi scheme like ICOs. And why not when people can earn 100%, 200%, 900%  returns in such a short time.  It's a very interesting dynamic but it's only one piece of the 'blockchain' and cryptocurrency puzzle.   As they say it's like we are early stages of the 1993 internet but wth the 1998 Hype cycle.   The investment money is driving the hype, but the technology will change the future.  People just don't realize it yet. Most people don't even know what this is and the banks are so fearful they are trying to create their own private blockchain consortium.  

   

Cryptocurrencies as legal tender is the defacto Bitcoin and blockchain answer and use case.  It's a ledger. It's secure. It's transparent. It's immutable.  It's mined. It's decentralized. It's a currency.  But the blockchain isn't just about monetary value or currency. In fact, most of the cryptocurrency movement isn't currency at all, it's a speculative investment just like anybody who buys stock in Tesla or Apple.  The real difference is some people can actually go and buy a pizza with BTC ; whereas owning stocks in Tesla is a complicated process to get it out.  

     Speaking of values and currency worth, who wants to buy a pizza with 1 BTC if it could be worth double tomorrow?  Or triple.  And when certain altcoins go up in value by 900%, it's a fascinating ride, and makes sense.  However, what happens when this all comes crashing down?  And we know it all will.  That's where we will see the real changes, the real players, the real interest.   The real fallout and disruption.  The fake players will disappear onto the next assumed hype cycle.  The real players will actually try and change the world.  It's so new and exciting that who doesn't want to be a part of this change.  This decentralized change coming.

     It's hype times a million right now and many people who couldn't even tell you what Bitcoin or the blockchain is, have invested in it.  It's money. It's a lot of money.  And it'll probably keep going up.  But maybe it won't.   Or maybe it will.

     Things like Ubiq smart contracts and Ethereum smart contracts are really the way of the blockchain future.  How do you get normal everyday people to care?  The internet didn't really become a defacto standard till smart mobile phones.  True people used AOL and prodigy and compuserve, but nobody cared or needed it. And the connections were too slow and not always on.  Many people assumed the internet was just a fad.   Email changed a lot of dynamics because everybody suddenly had a way of sending messages without  paying for a stamp.  

     I digress into the internet and dot com era to bring you back to the blockchain era. Things will change. It's just too early to figure out how it will all play out, but it's not about connecting the rest of the world who don't have the internet or bank accounts.  Oh that will make things progress faster. It'll make a few people millions or billions of dollars.  But the blockchain will change the world. And the centralized middle man will fall.  And smart contracts, the blockchain, cryptocurrency, automation, machine learning, AI, and IOT will bring a new future we never even imagined.   

The future is coming, will you pretend it's not? 

     

At&T 5g expansion

At&T made a smart IoT city move and acquisition and want to expand across the IOT universe. 

South Korea IOT Smart City

South Korea launches a Smart IOT City network.  This is great. 

http://www.bbc.com/news/technology-36710667

IOT & Blockchain

A IOT blockchain based storage and system management system.

This sounds interesting, but early stages and a work in progress. 

Smart city iot more asia and india

Asia and India are pushing for and investing in Smart Cities and IOT while the USA is lagging behind. 

Some of it is legacy infrastructure and city/state /fed politics. Other factors include the US is filled with a lot of marketing hype and little implementation.
We will see how it all plays out. 

Smart Cities and IOT...

The 4Cs are crucial.

Collaboration
Community
Consistency
Community

IOT + AI equals cost transformation

http://www.techrepublic.com/article/how-hershey-used-the-cloud-to-deploy-iot-and-machine-learning-without-a-data-scientist/

And they didn't even have a data scientist. The IOT world plus AI for Twizzlers.

The complicated nature of confusing 5G

http://www.androidpolice.com/2017/02/10/what-is-5g-the-laymans-guide/

And Verizon is doing a 5G test pilot in these cities. 
Ann Arbor, Atlanta, Bernardsville, Brockton, Dallas, Denver, Houston, Miami, Sacramento, Seattle, and Washington, DC.

What that actually means and how Verizon defines it are unknown.  But 5G is interesting and challenging and exciting.  And coming. 

Internet of things and smart cities

http://m.scmp.com/tech/social-gadgets/article/2055272/thinxtra-roll-out-internet-things-network-hong-kong-next-year

Dreaming of a connected Things kind of world with Analytics of Things on top of in

    Analytics encompasses a few categories. At least it's been that way for quite some time now. We've all read about analytics based upon Descriptive, Diagnostic, Predictive and Prescriptive. But how does it relate to Analytics of things and the Internet of things?

     IoT & AoT is a new old world that's changing everything.  It's also aiming for a 5G and connected everything world.  An always on and connected smart world.  But is it really smart? And how is machine learning and analytics going to help improve our lives?  We don't really need more technology to automate our lives and steal our jobs and money.  That's not a connected world. That's a poverty stricken dystopian society.

   Descriptive analytics has been around for ages, even before machines and computers took over.  What we call Descriptive now was just Business Intelligence and Data Warehousing operational reporting a few years ago.   And before that it was really just standard reporting.  
 
      Diagnostic is really a step up from Descriptive, but with more emphasis on analyzing some data to figure out  if you're losing money or the energy bill went up in the winter and summer months.   Many times it's based on some sort of regression model if it's complex or simple arithmetic aggregation and summation formulas if no form of data science is involved.
   
     Predictive is as it kind of sounds, it tries to predict the future based on historical data and trends. It's not always an exact science and a lot of it depends on the data collected and analyzed.  Before "big data' and NoSQL and Hadoop it was really based on a lot of bad sample data that didn't always create a clear picture of your past or future.
 
       Prescriptive is relatively new as it tries to not only to predict the future, but be far more proactive and make actual recommendations based on historical data, trends, and learning patterns.   Amazon shopping cart or Netflix is simple examples of recommendation engines, but that's just scratching the surface.

     Going forward machine learning and deeper learning wants to not only recommend, but basically diagnose, recommend, predict, and choose what you can and should do in a variety of domains and circumstances.   Hollywood has created worlds and movies like this.  Sadly though, most of these movies were dystopian horror shows and not a utopian peaceful and happy world.

     This leads me into Internet of Things (IoT) and Analytics of Things (AoT) and how the smart connected world is kind of like the movies, except wouldn't we rather have a utopian society vs a dystopian one?

     The Internet of Things is far more complex than people realize. If you listen to some consulting firms or companies pushing their own hardware sensors or software they will just sell you on the theory of Dump all the data into AWS or Azure or collect the data from sensors and put it into hadoop or spark.  And then run some diagnostics and predictions.   And the magic of IoT and AoT comes into view.  Except it's far more complicated than that.  Far far more complicated and people seem to be ignoring the reality and truth to these theories.

     IoT means connected everything.  Some manufacturers are building out sensors on their devices for everything. Whether it's a John Deere or Ford or GE doesn't really matter as they want to sell you on buying their devices to build out this IoT connected world.  But what does that actually mean?

     You can buy a few cheap sensors yourself, a rasberry Pi, download some open source software and create your own 'Smart home" and driveway where you get some text message or email that turns on your video camera system if somebody steps in front of your home or drives up your driveway.

     Is this IoT?  It kind of is, but all those devices need to be connected via blue tooth and wifi or hardwired.   And your phone must use some Telco service to get access to that text or email.   Somebody had to create an app or site so you can view that camera and maybe even speak to that stranger from afar.  Think of it as somebody knocking at your door while you're at work, but you can talk to them like you're home.  

     What kind of analytics does a normal person really need for a smart home?  Well homes and buildings are rarely like phones. And why would we want them to be?   It's really not a good idea to be an Apple home where every single thing in your house is bought from and subscribed to Apple or Google(well Alphabet) or Samsung or Tesla.   So you have a Samsung TV, a GE fridge, an Apple TV, an android Phone,  Whirlpool washers and dryers, a Ring doorbell system, a VW car,  some other Garage door opener,  and so on and so forth   All these devices should work together in theory. But we all know the enterprise space is filled with Microsoft products that don't exactly integrate or work with other Microsoft products.

     Now imagine adding Hadoop, Teradata, Oracle, HP, SalesForce, Vmware,  Cisco,  some local T1 and Internet provider,  some local security force, some company that maintains the elevators,  some 3rd party contractors, various lighting systems and air conditioners and heaters.   A smart building and a smart connected world is really as simple and as complex as it sounds.

     Even if we don't connect everything, connecting many things will require integration of hardware, software, sensors, and systems that have never been integrated before and many of these companies don't play nice with each other anyway.    And then building the analytics on top of all those different things.   There might be 20 different dashboards and KPIs that only matter to a few companies or individuals.  But in a IoT/AoT world, everything connected matters.  Except you just pay attention to what matters to you and finger point when the hardware or software isn't working.  That won't work though. People don't want to hear some rep blame somebody else.

    And lets not even get into how does the sensors or hardware hold up in Minnesota or Norway?   A mobile developer or web developer shouldn't care whether or not a sensor breaks down in freezing conditions.  Except a connected world means your mobile app is useless if the sensors can't survive under 32 degrees. Or above 100.  Or 10,000 feet in the sky.  Or over 55 MPH.  Or in an ocean. Or can't handle 1000 people a day pushing on actual elevator buttons. Or kids jumping up and down on a bed a thousand times a day.

      Or how do you pipe billions and billions of sensor data through the airwaves all over the world?  We have issues at times with electricity now. And that's in places like the US.  There are many countries where running water and electricity aren't exactly guaranteed every day.   So if they can't guarantee electricity, how are they going to guarantee Data and connectivity?   Smart connected devices and IoT isn't just buy some sensors, connect them, configure your software and do some analytics.  

     The Internet of Things and Analytics of Things will change the world.  It'll also be a complicated and connected system that isn't easy to implement or maintain.  Glossing over these realities helps nobody. It just creates a fake connected IoT/AoT world.  And that helps nobody but a few people and their bank accounts.

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Data science for IoT

What is Data Science for
the Internet of Things (IoT) ?  

Some good details  and framework here.